code: def build_model(args, device, ckpt=None):
      print("==> Building model..")
      net = {
          "resnet": ResNet34,
          "densenet": DenseNet121,
      }[args.model]()
      net = net.to(device)
      if device == "cuda":
          net = torch.nn.DataParallel(net)
          cudnn.benchmark = True
  
      if ckpt:
          net.load_state_dict(ckpt["net"])
  
      return net
  
file_path: AdaBound/demos/cifar10/main.py
imports: from __future__ import print_function
  import torch.optim
  import torch.backends.cudnn
  import torchvision
  import torchvision.transforms
  import os
  import argparse
  from models import *
  from adabound import AdaBound
label_desc: Use image node_id 5 for calling a global function with example usage: build_model(args, device, ckpt) and returns: net